Examination of Current Developments in EV Battery Power Management Techniques

Niharika Purohit *
Department of Electrical Engineering, Shri Shankaracharya Technical Campus, Chhattisgarh, India.
Periodicity:January - March'2025

Abstract

Electric Vehicles (EVs) have occurred as a good solution to help the environmental impact of traditional internal combustion engine vehicles. Key to the success of EVs is efficient and reliable battery power management systems. Further, central to the efficiency and longevity of EVs are battery power management systems. Recent advances in battery technology, along with sophisticated power management algorithms, have significantly enhanced the performance, range, and lifespan of EV batteries. This paper provides a comprehensive review of the fundamentals in battery power management for EVs. It discusses advancements in Battery modelling, Battery state estimation (The state of charge (SOC) and state of health (SOH)), cell equalizers for voltage balancing and improved safety. Furthermore, it discusses the fault diagnosis methods. Additionally, it discusses predictive maintenance techniques and battery health monitoring systems to ensure the long-term reliability of EV batteries. The integration of artificial intelligence (AI) and machine learning (ML) algorithms for real-time data analysis and optimization of battery performance is also highlighted.

Keywords

Electric Vehicles (EV), Li-Ion Battery, Artificial Intelligence, Rechargeable Batteries, Battery Cycle Life.

How to Cite this Article?

Purohit, N. (2025). Examination of Current Developments in EV Battery Power Management Techniques. i-manager’s Journal on Power Systems Engineering, 12(4), 40-50.

References

[26]. Satish, P. P., & Kishore, T. S. (2023). AI and ML for intelligent battery management in the age of energy efficiency. International Journal for Recent Development in Science and Technology (IJRDST), 7 (6), 134-140.
[28]. Verasamy, M., Faisal, M., Ker, P. J., & Hannan, M. A. (2018). Charging and discharging control of Li-Ion battery energy management for electric vehicle application. International Journal of Engineering &Technology (IJET), 7(4), 482-486.
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